Advanced Decision Modeling for Real Time Variable Tolling – Development and Testing of a Data Collection Platform

Our current ability to forecast demand on tolled facilities has not kept pace with advances in decision sciences and technological innovation. The current forecasting methods suffer from lack of descriptive power of actual behavior because of the simplifications used in current economic decision models. These simplifications are in part due to the historical limitations on data collection. Today, we are seeing advances in the data collection technology that captures naturalistic behavior and this study is seeking to develop and test such technology. This will be the first phase of a naturalistic driving study on the topic of variable road tolling and decision making. This investigation extends the state of knowledge of decision modeling under risk and ambiguity by developing a mobile data collection platform for the capturing of naturalistic choice outcomes, associated environmental states, decision makers’ self-articulated perceptions of risk and assessments of ambiguity, and socio-economic attributes. This software/hardware development is the first step in advancing our ability to forecast future revenue sources in transportation. The data collection platform will be used in an extending study and will allow the study team to obtain insights for developing, testing and implementing new behavioral models that explicitly describe how we use imprecise information—in this case, ambiguous information signaled by variable toll lane charges—that are superior to those obtained to date. To support the empirical observations of driver choice of diverting to high occupancy toll (HOT) or non-HOT lanes in real-time, this study documents the development and testing of an in-vehicle perception acquisition device. The device is based on smartphone technology and its software is designed using the latest IOS release. Drivers will be able to upload the software application onto their existing smartphone or tablet. The widespread acceptance and use of smartphones and tablets allows the collection and transmission of decision data collected in real-time without installing or altering the drivers’ vehicles in any manner. This both increases the convenience—and perhaps the use of the application—and reduces the cost of data collection.

• Record URL:
  http://files.library.northwestern.edu/transportation/online/unrestricted/2012/MATC-KU-361.pdf
• 
• Supplemental Notes:
  • This research was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
• Corporate Authors:

  University of Iowa, Iowa City

  Public Policy Center
  Department of Civil and Environmental Engineering
  Iowa City, IA  United States  52242-1192

  Mid-America Transportation Center

  University of Nebraska-Lincoln
  2200 Vine Street, PO Box 830851
  Lincoln, NE  United States  68583-0851

  Research and Innovative Technology Administration

  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Authors:
  • Hanley, Paul
  • Sikka, Nikhil
  • Yu, Hai
  • Ma, Suyun
• Publication Date: 2012

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Report
• Features: Figures; References; Tables;
• Pagination: 45p

Subject/Index Terms

• TRT Terms: Automatic data collection systems; Decision making; Mathematical models; Real time information; Smartphones; Travel behavior; Variable tolls
• Subject Areas: Data and Information Technology; Highways; Planning and Forecasting; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01482567
• Record Type: Publication
• Report/Paper Numbers: 25-1121-0001-478
• Files: UTC, TRIS, RITA, ATRI, USDOT
• Created Date: May 24 2013 9:59AM